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Related Experiment Video

Updated: Apr 4, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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Assessing Imaging Response to Therapy.

Jeet Minocha1, Robert J Lewandowski2

  • 1Division of Interventional Radiology, Department of Radiology, University of California San Diego, 200 West Arbor Drive, #8756, San Diego, CA 92103-8756, USA.

Radiologic Clinics of North America
|September 1, 2015
PubMed
Summary
This summary is machine-generated.

Assessing cancer treatment response using imaging is vital for patient survival. This review covers criteria for evaluating radiologic response to locoregional therapies (LRTs), especially for liver cancer.

Keywords:
Computed tomography (CT)European Association for the Study of the Liver (EASL)MR imagingModified RECIST (mRECIST)Response assessmentResponse evaluation criteria in solid tumors (RECIST)World Health Organization (WHO)

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Area of Science:

  • Oncology
  • Radiology
  • Medical Imaging

Background:

  • Locoregional therapies (LRTs) are important cancer treatments, particularly for liver tumors.
  • Accurate assessment of treatment response is key, as it can predict patient survival.
  • Imaging is essential for evaluating tumor response to LRTs, but assessment can be complex.

Purpose of the Study:

  • To review the criteria for assessing radiologic response to LRTs.
  • To focus on imaging assessment following treatment for hepatocellular carcinoma.

Main Methods:

  • Review of existing literature and established criteria for imaging response assessment.
  • Focus on criteria applicable to locoregional therapies.
  • Special consideration for hepatocellular carcinoma treatment.

Main Results:

  • Various criteria exist for assessing imaging response to LRTs.
  • Hepatocellular carcinoma presents unique challenges in imaging response evaluation.
  • Evolving methodologies are continually refining assessment techniques.

Conclusions:

  • Standardized criteria are crucial for objective evaluation of LRT effectiveness.
  • Imaging plays a pivotal role in monitoring treatment outcomes and guiding clinical decisions.
  • Continued research is needed to refine imaging assessment in diverse cancer types and treatments.